Stabilising and optimising a primary closed-loop milling circuit feeding a flotation circuit using StarCS RNMPC

Coetzee, L.C.

doi:10.3182/20140824-6-za-1003.01396

Cited by 4 publications

(4 citation statements)

References 3 publications

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“…Implementing an HNMPC is similar to implementing an NMPC which is becoming easier to implement due to the increased availability of suitable vendor platforms (see e.g. [23]). What remains a challenge is to accurately model the plant to be controlled, and to keep this model up to date.…”

Section: Discussionmentioning

confidence: 99%

“…The model was validated for process control, meaning it is not accurate enough for green fields grinding mill circuit design, but is qualitatively accurate and can be used for predictive controller design. This model forms the basis for the controller package StarCS RNMPC of Mintek [23].…”

Section: Process Modelmentioning

confidence: 99%

“…The hydrocyclone feed density, CF D (t/m 3 ), is manipulated by the feed rate of water to the sump, SF W (m 3 /h). In this study, CF D is not directly controlled, but minimized where possible in order to maximise circulating load and increase classifier performance [23]. The two output variables are modelled as,…”

Section: Sump Modulementioning

confidence: 99%

“…The model made it possible to design the robust non-linear MPC of [3]. Although the controller was not feasible for online application at the time, technological improvements (in the form of multi-core processors) have made it possible to implement non-linear MPC controllers with complex models in real time [23]. A drawback of non-linear MPC controllers is that discrete components in the circuit cannot be integrated directly in the controller [24].…”

Section: Introductionmentioning

confidence: 99%

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Hybrid non-linear model predictive control of a run-of-mine ore grinding mill circuit

Botha

Roux

Craig

2018

Minerals Engineering

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A hybrid non-linear model predictive controller (HNMPC) is developed for a run-of-mine ore grinding mill circuit. A continuous-time grinding mill circuit model is presented with a hydrocyclone cluster as the primary classifier. The discrete-time component is the switching of hydrocyclones in the hydrocyclone cluster. The resulting model is a hybrid non-linear model with both continuous and discrete dynamics. A simulation of the HNMPC shows the advantages of using the hydrocyclone cluster as an additional manipulated variable. The advantages of the HNMPC is illustrated by comparing its performance to a non-linear MPC where no switching of hydrocyclones is possible. The genetic algorithm based HNMPC showed increased controller stability in its ability to incorporate discrete dynamics into the controller directly. The methods discussed in this paper can be used to incorporate different types of discrete dynamics into advanced grinding mill circuit controllers due to the modular presentation of the model and HNMPC controller design.

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Section: Discussionmentioning

confidence: 99%

Section: Process Modelmentioning

confidence: 99%

Section: Sump Modulementioning

confidence: 99%